Relaxation Time Correlation NMR for Mechanochemical in-situ Reaction Monitoring of Metal-Organic Frameworks
Bibliographic record
Abstract
We present a new methodology for real-time observation of mechanochemical transformations, based on a magnetic resonance method in which T1-T2* relaxation time correlation maps are used to track the formation of the popular metal-organic framework (MOF) materials Zn-MOF-74 and ZIF-8. This two-dimensional (2D) relaxation correlation measurement is a new method utilizing simple saturation recovery to obtain a T1-T2* spectrum representing different hydrogen environments. The 2D T1-T2* results show a change in signal amplitudes, and their coordinates, within the plots as the reaction progresses, confirming reaction completion. Static solid samples are usually considered difficult to measure because of their short-lived T2* signal and their common non-exponential decay. Using a new processing method, the signal from samples with non-exponential decay was quantified. The importance of key parameters such as the instrument deadtime, the recovery times, and magnetic field strength for the measurement of solids with a short-lived signal is established. This novel magnetic resonance measurement is important since it provides a simple and easy way to analyse an entire solid reaction mixture within its reaction vessel.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".